Data Engineering Consultant

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

As a Data Engineering Consultant within our Rx Payment Modernisation team, you will design, develop, and optimize next-generation data solutions that power and simplify financial transactions across our prescription services. In this role, you will build robust, high-performance, and scalable data architectures and pipelines that ensure secure, efficient, and modern pharmacy payment processing. You will leverage cloud-based platforms and explore innovative intelligent automations to turn complex transactional data into secure, high-value assets. This is an exciting opportunity to solve complex data challenges and directly contribute to making prescription medications more affordable and accessible.

Primary Responsibilities:

Design, build, and maintain scalable, reliable, and high-performance ETL/ELT pipelines to ingest, process, and load transaction and prescription data from diverse sources into data platforms

Create and optimize database schemas, relational designs, and dimensional data models to support analytics, payment reconciliation, and reporting applications

Design, develop, and deploy AI-powered solutions and intelligent automations to address complex business and transaction challenges, focusing on the responsible and ethical use of technology

Use enterprise-approved AI tools and modern data methodologies to streamline payment workflows, automate repetitive data validation tasks, and drive continuous operational improvement

Perform data analysis, profiling, data cleansing, and validation to ensure the accuracy, completeness, and overall quality of payment and healthcare data

Optimize and tune database queries, SQL code, storage structures, and partitioning strategies to ensure optimal system performance and cost-efficiency

Evaluate emerging trends in AI, machine learning, and data engineering to inform solution design and drive strategic innovation within the payment systems

Collaborate with software engineers, data scientists, and business stakeholders to understand payment data requirements and translate them into robust technical solutions

Implement robust error handling, monitoring, alerting, and logging systems to proactively identify and resolve data pipeline failures

Ensure strict compliance with enterprise data security, privacy, governance standards, and regulatory requirements (including healthcare and financial transaction security) throughout the data lifecycle

Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

Bachelor's degree in Computer Science, Information Technology, or a related field, or 4+ years of equivalent software/data engineering experience

4+ years of professional experience in data engineering, data pipeline development, or software engineering

2+ years of experience utilizing programming languages such as Python, or Java for data manipulation, analysis, or automated processing

2+ years of experience developing ETL/ELT solutions in cloud data environments (e.g., ADF, azure Databricks)

2+ years of experience with data profiling, cleansing, and dimensional modeling concepts

1+ years of experience exposure to working with MongoDB is an advantage

1+ years of experience designing, developing, or integrating AI-powered or automated solutions within production data workflows

1+ years of experience with knowledge of DevOps principles, version control (Git), and automated CI/CD deployment pipelines (e.g., Jenkins, Azure DevOps, GitHub Actions)

Preferred Qualifications:

Experience with Big Data framework tools such as Spark, or Kafka

Experience utilizing scheduling or orchestration tools (e.g., Apache Airflow, or Azure Logic Apps)

Experience working within the healthcare industry and familiarity with pharmacy benefits, payments, or claims data

Demonstrated ability to analyze complex data sets, troubleshoot system bottlenecks, and articulate technical solutions to both technical and non-technical stakeholders

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.